摘要
以灰分、全水分为煤样指标建模了煤炭发热量的非线性二次回归预测模型,通过测试及对比,该模型具有较高的预测精度,预测结果能够满足工程需要,预测效果优于线性回归模型及神经网络模型等。另外,该预测模型还具有容易程序实现、操作简便等特点。
The non-linear quadratic regression prediction model of coal calorific value was modeled with ash content and total moisture as the coal sample index.Through testing and comparison,the model has higher prediction accuracy,and the prediction results can meet engineering needs,and the prediction effect is better than linearity regression model and neural network model.In addition,the prediction model has the characteristics of easy program implementation and easy operation.
作者
王玥
王江荣
Wang Yue;Wang Jiangrong(College of Petrochemical Engineering,Lanzhou Petrochemical polytechnic,Lanzhou 730060,China)
出处
《水泥工程》
CAS
2018年第6期17-19,共3页
Cement Engineering
关键词
煤炭发热量
二次回归
线性回归
神经网络
预测
calorific value of coal
two regression
linear regression
neural network
prediction
